If you had access to twitter's data, what would you, 1. Expect distributions of mutes and blocks to look like? 2. Expect in a healthy, well-designed information env? 3. Do you think they are the same thing?
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Replying to @generativist
1. Mutes and blocks cut off networks pretty effectively to create dark forests or echo chambers, whatever you want to call them 2. Graphs are well connected with a low number of vertices between different clusters based on shared opinions
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Replying to @jdetle
Point #1 is really why I'm trying to design what I'm building to use blocks and mutes with stochastic expiration. I think the ability for networks to heal and remain dynamic is important. (I get a lot of pushback on that though)
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Replying to @generativist
Yeah, people don't like being told by a computer that they were wrong when they see the person they blocked show up again I think.
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Replying to @jdetle
Yes. Also comes off as very "techbro-presenting" even though there's a lot of evidence that suggests blocklists are a useful attack vector.
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My current solution is that the duration is a function of how frequently the person is blocked within the users social radius and some rules they can specify. E.g. Kat*e Hopk*ns isn't going to get unblocked any time soon.
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